I am hearing despite increased investment in AI tools and employer sponsored AI training, employees are feeling over-whelmed by the pressure to keep up.

In a survey of 1,020 employed U.S. adults by ResumeNow finds 44% say they feel overwhelmed by the pressure to learn and use AI at work, and the same share said they lack a clear path for building AI skills.

Thirty percent said they were likely to spend their own money to learn those skills because they worried about falling behind. That is a telling signal for employers: access to AI tools and training is only part of the answer. Employees also need to set clear expectations and practical guidance on where to begin.

What Is Driving the Feeling of Being AI-Whelmed?

Fear and distrust of AI is behind this lack of confidence using AI at work. In a research study conducted among 150 C-Suite leaders by the University of Phoenix, leaders were asked what the biggest barriers were to use AI, they shared:

Fear and distrust of AI 87%

Ethical and security risks 55%

Loss of critical thinking by over relying on AI 38%

When these 150 C-Suite leaders were queried about how they personally feel about using AI at work, University of Phoenix found a decline in confidence and optimism using AI at work over a two-year period. See Figure 1

Biggest Fear: I Don’t Know How to Start Using AI

The biggest fear causing workers to be AI-whelmed is not knowing where to start building AI skills. Using AI can feel intimidating and fearful about where and how to get started building AI skills.

This means leaders need to be intentional about creating a culture of safe experimentation using AI at work. This can start with understanding how to conduct small experiments using AI for a few aspects of one’s day to day job to improve the quality and efficiency of work.

The goal is thoughtful usage of AI not just increased usage of AI.

What Can You Do For AI-Whelmed Workers? Pay Attention to AI-Well-being

1. Build AI-Wellbeing into your definition of employee well-being. Employee well-being is typically defined in five areas, but I believe a new one needs to be added:

o Financial Well-Being

o Mental Health Well-being

o Social Well-Being

o Physical Well-Being

o Career Well-Being

o NEW AI-Well-Being

I think a new lever needs to be created: AI-Well-being defined as thoughtful , responsible and healthy usage of AI. This means helping employees understand what the organization expects them to do with AI in their job role. Which tools are approved? How to access employer funded AI training? Where could AI help in a job? What does safe and responsible usage actually? How do one’s human skills of judgement and critical thinking play out when using AI at work? Without clear direction, employees feel uncertain and AI-whelmed.

1. Give employees time to experiment. Invite teams to try approved AI tools for tasks such as organizing research, brainstorming options, or drafting meeting summaries. An AI challenge half-day could give employees dedicated time to test one use case and share what worked, what failed, and what they would change.

2. Have leaders role model their usage of AI. Ask a leader to walk through a real task: what she asked AI to do, how she checked the output, and whether it improved the quality or efficiency of her work. Seeing the judgment behind the result can make AI use less intimidating.

3. Connect AI training to each team’s work. Use team meetings to discuss how existing AI training applies to specific goals. Make approved tools, prompt examples, employee tips, and opportunities to ask questions easy to find in one place.

4. Showcase the AI training that is already offered at your company. Use regular team meetings to discuss how AI training maps to the group’s specific KPI’s. But even when the share of companies offering AI training doubled from last year to this year, 43% of workers cite a lack of relevant AI training materials, according to research from Workera.

As AI fluency becomes essential to finding and keeping a job, leaders must recognize that the pressure to build these skills can affect employee well-being. Training alone will not ease that pressure. Although the share of companies offering AI-specific skills training rose from 25% to 58% between 2025 and 2026, employees still face uncertainty about how to use AI in their jobs.

Leaders can reduce this feeling of being AI-whelmed by setting clear expectations for using AI at work, giving employees time to practice and most importantly having leaders role model how they experiment with AI in their jobs. Without support, feelings of being AI-whelmed, will impact overall employee well-being.

Welcome to Staying Human With AI, where I’ll explore how AI is changing work, leadership and the employee experience, and what it takes to keep people at the center of that transformation.

I want to start our conversation with an issue every leader needs to be aware of: The AI Gender Gap. While AI opportunities are growing rapidly, women are not benefiting equally.

LinkedIn research covering 15,000 companies across 27 countries found that women accounted for only 26% of U.S. AI hires in 2025, compared with 50% of hires in non-AI occupations.

The gap is even wider at the top. Globally, women hold only:

• 20% of “Head of AI” roles

• 18% of “Member of Technical Staff” roles

• 13% of C-suite positions at AI companies

Earlier this year, Raghu Krishnaiah, Chief Operating Officer of Phoenix Education Partners and I highlighted the AI Gender divide in an article, entitled, “3 Ways Companies Can Close the AI Gender Gap.” Research from the University of Phoenix conducted among 604 leaders and workers, found that women trailed men in AI use and confidence. While 48% of men said they needed to develop the skills to work effectively with generative AI, only 39% of women said the same.

That difference matters. Knowing how to collaborate with AI and demonstrate AI fluency is quickly now an essential workplace competency. PwC estimates that nearly 80% of companies are already using AI agents to increase productivity and efficiency.

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By the end of 2026, the average person will spend more meaningful conversational time with AI than with any single human in their life.

This prediction, made in a recent Thomson Reuters article on AI, caused me to ask,

“What does it mean to stay human while using AI?

That is the question I will explore in this Substack. I’ll weave together research, real-world examples, and leadership insights with perspectives from AI-native companies and leaders across HR, Talent, and Technology.

My focus will be on the human side of AI: the fears, barriers, resistance, and false starts people experience as they learn to work with AI and, importantly, the strategies leaders and organizations can use to overcome them.

Ultimately, I’ll explore how we can nurture and grow the human capabilities of judgment, curiosity, creativity, empathy, and critical analysis in an AI-powered workplace.

My Substack posts will explore a range of issues such as:

• AI Literacy as an Expectation for Employment: University of Phoenix reports that 73% of C-Suite leaders are mandating AI literacy. And 69% and 69% expect to embed AI literacy into performance management by the end of 2026. How is AI literacy defined and how to hire for this?

• AI Gender Gap: Lean In research finds women are 32% more likely than men to worry they would be seen as cheating for using AI at work. What can be done about this so woman are not left behind?

• AI Age Gap: University of Phoenix finds the younger the leader, the less hopeful they are about the impact of AI in the workplace. While 75% of Baby Boomer leaders report feeling hopeful about AI’s impact, that figure falls to 59% among Gen X leaders and just 47% among Millennial leaders. Does this age gap persist across industries and job roles?

• New AI Jobs: EY is hiring a new Head of Agent Economics, as the firm examines if their AI spending is delivering concrete business benefits. The new executive will lead EY’s AI value realization office. What other new jobs will be created as companies increase their AI investment?

• AI and the Ever Expanding Job: Recent research from HBR finds AI does not reduce work, it intensifies it. This can result in expanding workloads, cognitive fatigue, burnout and at times lower quality of work. What can leaders do to help employees integrate AI into their workflow without increasing burnout, and work creep?

One More Thing:

• AI and Compensation: Humans are starting to ask if I just manage a team of agents, will I still need to manage humans to get visibility and access to promotions? How will compensation evolve as managers manage agent only teams and hybrid teams of agents and humans?

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